Affymetrix GeneChip Microarray Preprocessing for Multivariate Analyses
Overview
Authors
Affiliations
Affymetrix GeneChip microarrays are the most widely used high-throughput technology to measure gene expression, and a wide variety of preprocessing methods have been developed to transform probe intensities reported by a microarray scanner into gene expression estimates. There have been numerous comparisons of these preprocessing methods, focusing on the most common analyses-detection of differential expression and gene or sample clustering. Recently, more complex multivariate analyses, such as gene co-expression, differential co-expression, gene set analysis and network modeling, are becoming more common; however, the same preprocessing methods are typically applied. In this article, we examine the effect of preprocessing methods on some of these multivariate analyses and provide guidance to the user as to which methods are most appropriate.
Takemoto Y, Ito D, Komori S, Kishimoto Y, Yamada S, Hashizume A BMC Bioinformatics. 2024; 25(1):221.
PMID: 38902629 PMC: 11188187. DOI: 10.1186/s12859-024-05840-4.
Johnson K, Krishnan A Genome Biol. 2022; 23(1):1.
PMID: 34980209 PMC: 8721966. DOI: 10.1186/s13059-021-02568-9.
Farrow E, Chiocchetti A, Rogers J, Pauli R, Raschle N, Gonzalez-Madruga K Transl Psychiatry. 2021; 11(1):492.
PMID: 34561420 PMC: 8463588. DOI: 10.1038/s41398-021-01609-y.
Bime C, Pouladi N, Sammani S, Batai K, Casanova N, Zhou T Am J Respir Crit Care Med. 2018; 197(11):1421-1432.
PMID: 29425463 PMC: 6005557. DOI: 10.1164/rccm.201705-0961OC.
Cangelosi D, Muselli M, Parodi S, Blengio F, Becherini P, Versteeg R BMC Bioinformatics. 2014; 15 Suppl 5:S4.
PMID: 25078098 PMC: 4095004. DOI: 10.1186/1471-2105-15-S5-S4.